code: def test_get_info_gym_env(self, multithreading):
      num_envs = 5
      rng = np.random.RandomState()
      gym_env = self._make_batched_mock_gym_py_environment(
          multithreading, num_envs=num_envs
      )
      gym_env.reset()
      info = gym_env.get_info()
      self.assertEqual(info, {})
      action = np.stack(
          [
              array_spec.sample_bounded_spec(self.action_spec, rng)
              for _ in range(num_envs)
          ]
      )
      gym_env.step(action)
      info = gym_env.get_info()
      self.assertAllEqual(info["last_action"], action)
      gym_env.close()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import random_py_environment
  from tf_agents.specs import array_spec
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 7 for calling the BatchedPyEnvironmentTest obj's underlying member method code with example usage: obj.test_get_info_gym_env(multithreading) without return types